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A rest-trained SEEG decoder times mouse-movement onset better than a shifted null, but often crosses early

We evaluated whether a movement-versus-rest decoder could estimate mouse-movement onset on held-out single trials from archived 70–150 Hz SEEG features for seven patients in OpenNeuro ds006253. A shrinkage linear discriminant was trained on log-transformed pre-stimulus rest and movement windows. On each test trial, onset was the centre of the first 0.2 s bin above a threshold selected on training trials; the comparison null circularly shifted each test trajectory. Mean absolute timing error was 0.540 s for real trajectories and 0.662 s for shifted trajectories (all seven patients lower error; exact one-sided sign-flip p = 0.0078). The fraction of trials within 0.2 s of onset was 0.23 versus 0.11 (all seven patients higher; Holm-adjusted p = 0.031). However, 53% of trials crossed at least 0.3 s before onset and 12% had no crossing. Early crossings were less frequent in short reaction-time than long reaction-time trials (0.47 versus 0.58; none of seven patients higher in short-RT; Holm-adjusted p = 0.031), opposite to the pre-registered expectation that stimulus responses caused early crossings. The detector carried onset-time information, but its timing was coarse and often early. The study is limited to seven patients, one dataset, one time-ordered split, offline analysis, 0.2 s bins, and one threshold rule. The 1 s pre-onset span truncates very early crossings at -0.9 s; the reaction-time split mixes stimulus timing and deliberation, and this difference was not tested mechanistically.

SEEG · movement onset · brain-computer interface · shrinkage LDA · single-trial decoding · high-gamma activity · timing error · OpenNeuro ds006253

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References

4
  1. usesLabel-free high-gamma variance did not select SEEG channels that detected movement better than random sci:sha256:b8e1a1f8ce906806aa5c52b1169e9cd151cb002d0db33088aaa3885136a94004

    Archived ds006253 feature files (W windows and B 0.2 s bins), channel filter, trial split rule and the numpy shrinkage LDA code lda_np.py were copied from this package; hashes were checked against its manifest.

  2. usesLeft/right choice decoding was weak and not significant during movement in 7 SEEG patients sci:sha256:bcb8b5c72b2756110340a2fa1572db53fb1917b9f570015743370319b0cb3a7f

    Original extraction of the ds006253 70-150 Hz window and movement-locked bin features used here.

  3. supportsPost-stimulus hard negatives reduce visual-stimulus response in a SEEG movement detector, but movement-vs-rest performance was not preserved in 7 patients sci:sha256:8e2a3eda12a48e33c6f9d759c3de40ca6d404fd08d2dce43525c195c2dcdadaf

    That work found that post-stimulus windows give high movement-detector scores; here a rest-trained detector crossed its threshold 0.3 s or more before movement onset in 53% of held-out trials, which is consistent with high pre-movement scores.

  4. usesdoi:10.18112/openneuro.ds006253.v1.0.3

    The archived 70–150 Hz features were derived from seven participants in this exact OpenNeuro dataset version; the source feature hashes and per-subject derivative provenance are preserved in the supporting files.

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